Protocol for comparing gene-level selection on coding mutations between two groups of samples with Coselens

19 Pág.The study of genes that evolve under conditional selection can shed light on the genomic underpinnings of adaptation, revealing epistasis and phenotypic plasticity. This protocol describes how to use the Coselens package to compare gene-level selection between two groups of samples. After installing Coselens and preparing the datasets, a typical run on a laptop takes less than 10 min. Coselens is best suited to analyze somatic mutations and data from experimental evolution, for which independently evolved samples are available. For complete details on the use and execution of this protocol, please refer to Iranzo et al. (2022).1.J.I. is supported by the Agencia Estatal de Investigación of Spain (Grant No. PID2019-106618GA-I00), the Ramón y Cajal Programme of the Spanish Ministry of Science (Grant No. RYC-2017-22524), the Severo Ochoa Programme for Centres of Excellence in R&D of the Agencia Estatal de Investigación of Spain (Grant No. CEX2020-000999-S (2022–2025) to the C.B.G.P.), and the Comunidad de Madrid (through the call Research Grants for Young Investigators from Universidad Politécnica de Madrid, Grant No. M190020074JIIS). G.G. is supported by the DHHS/PHS/National Institutes of Health (Grant No. 2R01DE019637-10, “Patterning the vertebrate dentition through replacement and repair). J.C.-E. is supported by the Youth Employment Initiative of the European Social Fund through a junior postdoctoral contract from Comunidad de Madrid (Grant No. PEJD-2019-POST/BIO-16377) and the Margarita Salas program of the Ministry of Universities of Spain (CT31/21). E.V.K. is supported by intramural research program funds of the National Institutes of Health (National Library of Medicine).With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2020‐000999‐S)Peer reviewe

Pervasive conditional selection of driver mutations and modular epistasis networks in cancer

23 Pág. Centro de Biotecnología y Genómica de PlantasCancer driver mutations often display mutual exclusion or co-occurrence, underscoring the key role of epistasis in carcinogenesis. However, estimating the magnitude of epistasis and quantifying its effect on tumor evolution remains a challenge. We develop a method (Coselens) to quantify conditional selection on the excess of nonsynonymous substitutions in cancer genes. Coselens infers the number of drivers per gene in different partitions of a cancer genomics dataset using covariance-based mutation models and determines whether coding mutations in a gene affect selection for drivers in any other gene. Using Coselens, we identify 296 conditionally selected gene pairs across 16 cancer types in the TCGA dataset. Conditional selection affects 25%-50% of driver substitutions in tumors with >2 drivers. Conditionally co-selected genes form modular networks, whose structures challenge the traditional interpretation of within-pathway mutual exclusivity and across-pathway synergy, suggesting a more complex scenario where gene-specific across-pathway epistasis shapes differentiated cancer subtypes.J.I. is supported by the Ramón y Cajal Program of the Spanish Ministry of Science (grant no. RYC-2017-22524), the Agencia Estatal de Investigación of Spain (grant no. PID2019-106618GA-I00), and the Severo Ochoa Program for Centers of Excellence in R&D of the Agencia Estatal de Investigación of Spain (grant no. SEV-2016-0672 [2017–2021] to the CBGP). G.G. is supported by the DHHS/PHS/National Institutes of Health (grant no. 2R01DE019637-10, “Patterning the vertebrate dentition through replacement and repair”). J.C.-E. is supported by the Youth Employment Initiative of the European Social Fund through a junior postdoctoral contract from Comunidad de Madrid (grant no. PEJD-2019-POST/BIO-16377). E.V.K. is supported by intramural research program funds of the National Institutes of Health (National Library of Medicine).Peer reviewe

Cellular profiling of a recently-evolved social behavior in cichlid fishes

Abstract Social behaviors are diverse in nature, but it is unclear how conserved genes, brain regions, and cell populations generate this diversity. Here we investigate bower-building, a recently-evolved social behavior in cichlid fishes. We use single nucleus RNA-sequencing in 38 individuals to show signatures of recent behavior in specific neuronal populations, and building-associated rebalancing of neuronal proportions in the putative homolog of the hippocampal formation. Using comparative genomics across 27 species, we trace bower-associated genome evolution to a subpopulation of glia lining the dorsal telencephalon. We show evidence that building-associated neural activity and a departure from quiescence in this glial subpopulation together regulate hippocampal-like neuronal rebalancing. Our work links behavior-associated genomic variation to specific brain cell types and their functions, and suggests a social behavior has evolved through changes in glia